Instruction Stream Fetch Request Coalescing for Memory Efficiency
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Solution Overview
Problem
Current data processing systems face inefficiencies when reading data from memory, especially when cache coherence cannot be maintained due to non-snoopable memory writes, leading to incorrect data retrieval for sequential fetch requests.
Innovation Solution
The system coalesces sequential fetch requests into longer requests that match the system memory interface width, ensuring data correctness by reading only after it is available in memory, and orders the data according to the original fetch requests, even across different data classes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a cache is used to store data read from memory, then memory access efficiency is improved for sequential fetches, but cache coherence cannot be maintained when memory writes are non-snoopable, leading to incorrect data retrieval
Solution Approach 1:
The patent removes the cache from the system entirely, extracting the problematic component that causes coherence issues. By eliminating the cache, the system avoids the complexity of maintaining coherence with non-snoopable memory writes while still achieving efficient sequential data fetching through alternative means.
Solution Approach 2:
The patent performs preliminary actions by validating data availability in memory before initiating fetch operations. The system ensures data is ready and correct before reading, preventing incorrect data retrieval without requiring cache coherence mechanisms. This is achieved through readiness validation and ordering guarantees that ensure data is fetched only when correct and available.
2Reliability
If sequential fetch requests are processed individually, then data correctness is maintained, but memory access efficiency deteriorates due to multiple small reads instead of optimized bulk reads
Solution Approach 1:
The patent merges multiple sequential fetch requests into a single optimized read operation. By combining individual fetch requests for different data classes into one bulk read when they are sequential and non-overlapping, the system achieves both data correctness and improved memory access efficiency, eliminating the need for multiple separate memory transactions.
Solution Approach 2:
The patent creates a universal fetch mechanism that handles multiple data classes through a single read operation. The system can read different data classes (vertex attributes, indices, etc.) in one memory transaction, making the memory access mechanism universally applicable to various data types while optimizing for both correctness and efficiency.
3Reliability
If fetch requests for different data classes are handled separately, then data correctness is maintained, but memory bandwidth utilization deteriorates due to interleaved requests
Solution Approach 1:
The patent combines interleaved fetch requests for different data classes into a single unified read operation when they are sequential and non-overlapping. This merging approach maintains data correctness by preserving the logical ordering of different data classes while dramatically improving memory bandwidth utilization by reducing the total number of memory transactions.
Solution Approach 2:
The patent performs preliminary sorting and validation of fetch requests before executing memory reads. By pre-ordering requests and validating data availability in advance, the system ensures correct data retrieval while enabling batched memory operations that maximize bandwidth utilization and reduce energy consumption.
Data Source
AI summary
Sequential fetch requests from a set of fetch requests are combined into longer coalesced requests that match the width of a system memory interface in order to improve memory access efficiency for reading the data specified by the fetch requests. The fetch requests may be of different classes and each data class is coalesced separately, even when intervening fetch requests are of a different class. Data read from memory is ordered according to the order of the set of fetch requests to produce an instruction stream that includes the fetch requests for the different classes.